Current Students

Zhiyuan Wei, Ph.D. student

Zhiyuan Wei is a third year Ph.D. student in the Department of Industrial & Systems Engineering at the University at Buffalo (SUNY). He holds a B.S. in Computer Science from Ludong University and a M.S. in Industrial Economics from University of International Business and Economics (UIBE) in 2016, China. He also obtained a M.S. in Industrial Engineering from University at Buffalo (SUNY) in 2019. Zhiyuan's research interests lie in risk analysis and informed decision making in the domain of public health.

  • 1) Dissertation (working title): A Transformative Data-centric Framework to Assess Community Resilience to Natural Disasters Leveraging Large-scale Human Mobility Data
  • 2) Wei, Z. and Mukherjee, S. (2020). “Health-behaviors associated with the growing risk of adolescent suicide attempts: A data-driven cross-sectional study”, Journal of Health Promotion Research  (PMID: 33297721)
  • 3) Mukherjee, S. and Wei, Z. (2021). “Suicide disparities across metropolitan areas in the U.S.: A comparative assessment of socio-environmental factors using a data-driven predictive approach”, PLOS One (forthcoming)
  • 4) Mukherjee, S., Shucard, J., Rintamaki, L., Wei, Z., Carlasare, L., and Sinsky, C. (2021). “The Invisible COVID-19 Crisis: Post-Traumatic Stress Disorder Risk Among Frontline Physicians Treating COVID Patients”, Journal of Psychiatric Research (under review)
Prasangsha Ganguly, Ph.D. student

Prasangsha Ganguly is a third year Ph.D. student in the Department of Industrial & Systems Engineering at the University at Buffalo (SUNY). He obtained a Bachelor of Technology Degree in Computer Science from West Bengal University of Technology, Kolkata, India in 2015, and a Master of Technology degree in Disaster Mitigation and Management from Indian Institute of Technology Roorkee, India, in 2017. His research interests lie in area of applied data science and operations research.

  • 1) Dissertation (working title): Resilience and Vulnerability Analysis of Electricity Infrastructure System Under Adverse Climate Conditions
  • 2) Awarded 2021 Natural Hazards Student Research Grant from Center for Geohazards Study
  • 3) Ganguly, P.; and Mukherjee, S. (2021). “A Multifaceted Risk Assessment Approach Using Statistical Learning to Evaluate Socio-environmental Factors Associated with Regional Felony and Misdemeanor Rates”, Physica A: Statistical Mechanics and its Applications; Volume 574, 15 July 2021, 125984
  • 4) Masoudvaziri, N. , Ganguly, P., Mukherjee, S., Sun, K. (2021) “Impact of geophysical and anthropogenic factors on wildfire size: A spatiotemporal data-driven risk assessment approach using statistical learning”, Stochastic Environmental Research and Risk Assessment journal (forthcoming)
  • 5) Mukherjee, S.; Boamah, E.F.; Ganguly, P.; and Botchwey, N.; (2021) “Towards resilient mental wellbeing in cities: A data-driven learning from mental health-environment nexus”, Nature Scientific Reports, 11, 17548 (2021)
  • 6) Ganguly, P., and Mukherjee, S. (2021) “Understanding Wildfire Induced Risk on Interconnected Infrastructure Systems Using a Bow-Tie Model and Self Organizing Maps”, In the proceedings of the 31st European Safety and Reliability Conference (ESREL 2021), France Angers, Sep 19-23, 2021; DOI: 10.3850/978-981-18-2016-8_567-cd
  • 7) Masoudvaziri, N. , Ganguly, P., Mukherjee, S., Sun, K. (2020) “An integrated risk-informed decision framework to minimize wildfires-induced power outage risks”, In the Proceedings of the 30th European Safety and Reliability Conference (ESREL 2020), Venice Italy, Nov 1-6, 2020; ISBN/DOI: 978-981-14-8593-0 
Yashraj Shashikant Sharma, Ph.D. student

Yashraj Sharma is a second year Master’s student in the department of Industrial and Systems Engineering at the State University of New York at Buffalo. He obtained his Bachelor’s in Industrial Engineering from Shri Ramdeobaba college of Engineering and Management, Nagpur, Maharashtra, India in 2021. He is curious about and fascinated by how Operations Research and Machine Learning can help solve complex problems and my research interests lie in applying these techniques to tackle real-world scenarios.

Pranav Vinod Pillai, M.S. student

Pranav Pillai is a second year Master's degree student in the Department of Industrial and Systems Engineering at the University at Buffalo (SUNY) . He obtained a B.S in Chemical and Biological Engineering from the University at Buffalo (SUNY) in 2021 . His research interests lie in Operations Research, Machine Learning and Data Analytics in the domain of disaster management.


Aishwarya Gupta, M.S. student

Aishwarya was a Master's student in the Department of Industrial and Systems Engineering at the University at Buffalo (SUNY). She holds a bachelor's degree in Industrial Engineering from Ramdeobaba college of engineering and management (RCOEM) , Nagpur University, Maharashtra, India in 2018. Aishwarya's interests lie in statistical analysis, predictive modeling and operations research to solve real time problems.

  • 1) Placement: Program manager Safety & Compliance at Amazon
  • 2) M. S. Thesis:  “Investigating Public Sentiment Towards Government-Issued COVID-19 Policies and Mandates Through Twitter Lens: A Data-Centric Approach”, MS Thesis 2021
  • 3) Conference presentation: Wei, Z., and Mukherjee, S. (2020) “Investigating People’s Reactions Towards Government Policies During COVID-19 Using Sentiment Analysis of Twitter Data”, Oral presentation at the Society for Risk Analysis Annual Meeting (virtual)
Ziyu(Bryce) Zhong, Undergraduate student

Bryce is pursuing a bachelor’s degree from the University at Buffalo (SUNY), and he is currently a senior in Computer Science Engineering. He is going to continue to pursue a master's degree in STEM fields after graduation. His research interest is to solve real-world problems by studying algorithms. He continued to pursue his graduate studies (MS in Security Informatics) at Johns Hopkins University.

Saumya Pandey, Undergraduate student

Saumya is pursuing a Bachelor’s Degree in Statistics, with a minor in Computer Science and Mathematics. After graduation, she is going to pursue a Master’s degree in Statistics. Her research interests lie in using statistical and machine learning techniques in solving real-world problems.